![]() We recently addressed the matter of fairness in algorithmic recommendations, questioning how fair and balanced the algorithmic landscape is. There's not enough space on that premium editorial shelf to go around. Of course, not all of these tracks are frontline commercial priorities: a healthy chunk of that 70k figure can be attributed to DIY micro-releases and "deep cuts" catalog uploads. Which means that the Spotify editorial can accommodate only a tiny fraction of the ever-growing volume of "70,000 tracks uploaded on Spotify every day". We assess that these ~5000 frontline playlists have a total capacity of about 350,000 tracks, with most tracks staying on the playlist for months on end. As of 2022, Spotify curated about 5,000 frontline official playlists (frontline meaning that at least 75% of tracks in these playlists are recent additions released in the past 18 months). Yet, the space on editorial playlists is still very much finite - and extremely valuable. The results? In its Made to be Found report released earlier this year, Spotify claimed that between 20, more than 150,000 artists were added to a Spotify editorial playlist for the first time - which is nothing to sneeze at. Spotify's curators are perhaps the most approachable out of all the major streaming platforms - since 2018, every artist has had direct access to Spotify editorial through the Spotify for Artists pitch form. And, with the editorial deck seemingly stacked in favor of major-backed artists, the indies questioned the fairness of the editorial system, wondering what the editorial game is really about: music or partnerships, scale, and power? Over the years, a New Music Friday addition on release day has been a must-have token of any Triple-A campaign, while emerging artists went all out to get their music in front of the editorial teams and secure any editorial support. With the streaming economy at its peak, playlists - and, especially, editorial playlists, have become a critical promotion channel for most artists in the business. ![]() Analysis by Julie Knibbe - Research and findings led by Parth Sinha and Pavel Telica
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